boolis_bigendian #大端模式 uint32point_step #点的长度(以字节为单位),计算方式是:point_step=len(fields)*datatype uint32row_step #通过一下公式计算:total_number_of_points = height * width,row_step = total_number_of_points * point_step uint8[] data #是一个一维数组,二进制点云流,不直观,...
sensor_msgs::PointCloud2是 ROS 中用于表示点云数据的标准消息类型。它支持多种点字段,可以用于表示复杂的点云数据,包括x、y、z坐标以及其他自定义字段(如intensity、rgb、normal_x等)。 数据结构 字段定义: 使用std::vector<sensor_msgs::PointField>存储字段信息,每个字段描述点的数据类型、偏移量、名称等。 ...
PointCloud2的data是序列化后的数据,直接看不到物理意义,可以转到PointCloud处理 #include<sensor_msgs/PointCloud2.h>#include<sensor_msgs/PointCloud.h>#include<sensor_msgs/point_cloud_conversion.h>sensor_msgs::PointCloud clouddata; sensor_msgs::convertPointCloud2ToPointCloud(msg, clouddata); sensor_m...
void mmwHandler(const sensor_msgs::PointCloudConstPtr& mmwCloudMsg){mBuf.lock();// rawMMWCloudQueue.push_back(mmwCloudMsg);sensor_msgs::PointCloud2 laserCloudMsg;convertPointCloudToPointCloud2(*mmwCloudMsg, laserCloudMsg);laserCloudMsg.header.stamp = mmwCloudMsg->header.stamp;laserCloudMsg.head...
After subscribing to a PointCloud2 message in ROS2, I want to extract the PointCloud2 points from the message. In ROS1 I could do that with: sensor_msgs.point_cloud2.read_points(). However, point_cloud2 seems to be missing from sensor_msgs in ROS2. Here is the basic code I am...
使用sensor_msgs::convertPointCloud2ToPointCloud和sensor_msgs::convertPointCloudToPointCloud2. 那么如何在ROS中使用PCL呢? (1)在建立的包下的CMakeLists.txt文件下添加依赖项 在package.xml文件里添加: <build_depend>libpcl-all-dev</build_depend><run_depend>libpcl-all</run_depend> ...
from sensor_msgs.msg import LaserScan, PointCloud2, PointField import numpy as np import open3d as o3d def points_to_pointcloud2(points, frame_id): msg = PointCloud2() msg.header.frame_id = frame_id msg.height = 1 msg.width = len(points) ...
(camera_point.x()); points.push_back(camera_point.y()); points.push_back(camera_point.z()); } } } int n_points = points.size(); // Create a PointCloud2 sensor_msgs::PointCloud2 cloud_msg; sensor_msgs::PointCloud2Modifier ...
ObservationBuffer是一个障碍物观察数据的buffer。观测到的障碍物数据都将转成sensor_msgs::msg::PointCloud2格式,然后存储到ObservationBuffer中。 在ObservationBuffer里存储的历史障碍物数据可以根据想保持的时间来清空。期望保持的时间主要由变量observation_keep_time_来决定。如果设置成rclcpp::Duration(0.0s)则表示每次...
1. ros的订阅sensor_msgs::PointCloud2的topic保存为.pcd格式点云 1.1. rostopic查看主题名称 rostopic list -v 1.2. 启动pcl_ros包下的pointcloud_to_pcd节点保存点云 rosrun pcl_ros pointcloud_to_pcd /input:=/globalmap 注意: 参数/input:=/global_map 中的/global_map 改为你需要保存的topic。